Hyperspectral imaging for automated inspection
of offshore wind infrastructure
This research explores the benefits of hyperspectral and other optical imaging techniques for offshore wind turbine inspection. These camera technologies would be a safer and less expensive alternative to manual inspections.
Currently, inspections of offshore wind turbines are performed by specialised personnel. These inspections are dangerous, costly, and the quality depends heavily on the experience of the inspector. Due to these high costs, continuous monitoring of corrosion or coating is not possible.
We therefore propose a solution using hyperspectral cameras that can be mounted on drones or other mobile platforms, allowing continuous monitoring of the condition of wind turbines.
Hyperspectral cameras (HSI) are cameras that capture hundreds of wavelengths simultaneously, as opposed to the three (red, green and blue) of a standard (RGB) camera. Therefore, we have much more information available to analyse the current state of the wind turbine
Three different experiments will be performed:
Corrosion detection based on mineral analysis. The amount and type of minerals present in the corrosion products provides information on whether the corrosion is active (bad) or more passive (good).
Inspection of the coating curing process and the coating mixture. Since we measure the 'chemical information' of the coating, we can use it to predict the curing time of the coating or incorrect coating mixes.
Evaluation of coating degradation. The chemical composition of the coating changes and is easier to see with a HSI camera.
In this PhD, we will investigate which camera technology is best for corrosion detection, coating curing process, and coating degradation process.